Submission¶

Put the ipynb file and html file in the github branch you created in the last assignment and submit the link to the commit in brightspace

In [1]:
from plotly.offline import init_notebook_mode
import plotly.io as pio
import plotly.express as px

init_notebook_mode(connected=True)
pio.renderers.default = "plotly_mimetype+notebook"
In [2]:
#load data
df = px.data.gapminder()
df.head()
Out[2]:
country continent year lifeExp pop gdpPercap iso_alpha iso_num
0 Afghanistan Asia 1952 28.801 8425333 779.445314 AFG 4
1 Afghanistan Asia 1957 30.332 9240934 820.853030 AFG 4
2 Afghanistan Asia 1962 31.997 10267083 853.100710 AFG 4
3 Afghanistan Asia 1967 34.020 11537966 836.197138 AFG 4
4 Afghanistan Asia 1972 36.088 13079460 739.981106 AFG 4

Question 1:¶

Recreate the barplot below that shows the population of different continents for the year 2007.

Hints:

  • Extract the 2007 year data from the dataframe. You have to process the data accordingly
  • use plotly bar
  • Add different colors for different continents
  • Sort the order of the continent for the visualisation. Use axis layout setting
  • Add text to each bar that represents the population
In [3]:
# YOUR CODE HERE

pop_2007 = df[df['year'] == 2007]
pop_2007_continent = pop_2007.groupby('continent').sum() #.reindex()
# pop_2007_continent = pop_2007_continent.sort_values('pop', ascending=False)
pop_2007_continent = pop_2007_continent.reset_index()
pop_2007_continent.head()

px.bar(
    data_frame=pop_2007_continent, 
    x='pop',
    y='continent',
    color='continent',
    orientation='h',
)
In [4]:
pop_2007 = df[df['year'] == 2007]
pop_2007_continent = pop_2007.groupby('continent').sum().reindex()
# pop_2007_continent = pop_2007_continent.sort_values('pop', ascending=False)
pop_2007_continent = pop_2007_continent.reset_index()
# pop_2007_continent.head()

Question 2:¶

Sort the order of the continent for the visualisation

Hint: Use axis layout setting

In [5]:
# YOUR CODE HERE

pop_2007 = df[df['year'] == 2007]
pop_2007_continent = pop_2007.groupby('continent').sum().reindex()
pop_2007_continent = pop_2007_continent.sort_values('pop', ascending=False)
pop_2007_continent = pop_2007_continent.reset_index()
# pop_2007_continent.head()

px.bar(
    data_frame=pop_2007_continent, 
    x='pop',
    y='continent',
    color='continent',
    orientation='h',
)

Question 3:¶

Add text to each bar that represents the population

In [6]:
# YOUR CODE HERE

pop_2007 = df[df['year'] == 2007]
pop_2007_continent = pop_2007.groupby('continent').sum().reindex()
pop_2007_continent = pop_2007_continent.sort_values('pop', ascending=False)
pop_2007_continent = pop_2007_continent.reset_index()
# pop_2007_continent.head()

px.bar(
    data_frame=pop_2007_continent, 
    x='pop',
    y='continent',
    color='continent',
    orientation='h',
    # text_auto=True,
    text_auto='.2s',
    # text='pop',
)

Question 4:¶

Thus far we looked at data from one year (2007). Lets create an animation to see the population growth of the continents through the years

In [13]:
pop = df.groupby(['year', 'continent']).sum().reindex()
# pop = pop.sort_values('pop', ascending=False)
pop = pop.reset_index()
pop.head()

fig = px.bar(
    data_frame=pop,
    x='pop',
    y='continent',
    color='continent',
    animation_frame="year", 
    animation_group="continent",
    orientation='h',
    range_x=[0,4_000_000_000]
)
fig = fig.update_layout(barmode='stack',yaxis={'categoryorder':'total ascending'},showlegend=False)
fig.show()

Question 5:¶

Instead of the continents, lets look at individual countries. Create an animation that shows the population growth of the countries through the years

In [11]:
# YOUR CODE HERE
pop = df.groupby(['year','country'])['pop'].sum().reset_index()

fig = px.bar(
    data_frame=pop,
    x='pop',
    y='country',
    color='country',
    animation_frame='year',
    animation_group='country',
    orientation='h',
    range_x=[0,1_500_000_000]
)
fig = fig.update_layout(barmode='stack',yaxis={'categoryorder':'total ascending'},showlegend=False)
fig.show()

Question 6:¶

Clean up the country animation. Set the height size of the figure to 1000 to have a better view of the animation

In [12]:
# YOUR CODE HERE

# pop = df.sort_values('year', ascending=True)
pop = df.groupby(['year','country'])['pop'].sum().reset_index()

fig = px.bar(
    data_frame=pop,
    x='pop',
    y='country',
    color='country',
    animation_frame='year',
    # sort_values='year',
    animation_group='country',
    orientation='h',
    range_x=[0,1_500_000_000],
    height=1000,
)
fig = fig.update_layout(barmode='stack',yaxis={'categoryorder':'total ascending'},showlegend=False)
fig.show()

Question 7:¶

Show only the top 10 countries in the animation

Hint: Use the axis limit to set this.

In [10]:
# YOUR CODE HERE

pop = df.groupby(['year','country'])['pop'].sum().reset_index()

fig = px.bar(
    data_frame=pop,
    x='pop',
    y='country',
    color='country',
    animation_frame='year',
    animation_group='country',
    orientation='h',
    range_x=[0,1_500_000_000],
    range_y=[132,142],
    height=300,
)
fig = fig.update_layout(barmode='stack',yaxis={'categoryorder':'total ascending'},showlegend=False)
fig.show()